Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ambient-code/platform --skill gerrit-reviewgit clone --depth 1 https://github.com/ambient-code/platformWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ambient-code/platform/gerrit-review)<a href="https://agentmods.dev/skills/ambient-code/platform/gerrit-review"><img src="https://agentmods.dev/badge/skills/ambient-code/platform/gerrit-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ambient-code/platform/gerrit-review"><img src="https://agentmods.dev/badge/skills/ambient-code/platform/gerrit-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.00797 |
| Opus 5.5 | $0.00025 | $0.00319 |
| Sonnet 5.5 | $0.00012 | $0.00159 |
| Haiku 4.5 | $0.00006 | $0.00080 |
Grade A, and why
gerrit-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- gerrit-review — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gerrit Code Review
Guide for reviewing changes on a Gerrit instance using the Gerrit MCP server tools.
Prerequisites
The Gerrit MCP server must be available (credentials configured via Integrations page). If mcp__gerrit__* tools are not listed, the user needs to connect their Gerrit instance first.
Workflow
1. Fetch the change
Use mcp__gerrit__fetch_gerrit_change with the change ID (numeric or change-Id).
Extract from the response:
- Subject and commit message — understand what the change does
- Owner — who authored it
- Status — NEW (open), MERGED, ABANDONED
- Current patch set number — the latest revision
- Files changed — list of modified files with insertions/deletions
- Existing comments — what reviewers have already said
- Labels — current votes (Code-Review, Verified, etc.)
2. Read the diffs
Use mcp__gerrit__fetch_patchset_diff to compare patch sets or view the current diff.
- To see the full change: compare patch set 1 vs current (or base vs current)
- To see what changed between review rounds: compare two specific patch sets
- Filter by file path if the change is large — focus on the most impactful files first
3. Analyze and form review feedback
Apply standard code review principles:
- Correctness — does the logic do what the commit message claims?
- Edge cases — missing null checks, boundary conditions, error handling
- Style — follows project conventions (check CLAUDE.md if available)
- Security — no credentials in code, proper input validation, no injection vectors
- Performance — unnecessary allocations, N+1 queries, missing caching
4. Post the review
Use mcp__gerrit__submit_gerrit_review to post feedback:
- message: A summary of your review findings (top-level comment)
- labels: Vote appropriately:
Code-Review +1— looks good but someone else should also reviewCode-Review +2— approved, ready to submit (only if you have authority)Code-Review -1— needs changes before mergingCode-Review -2— blocks submission (serious issues)Verified +1— tests pass, builds clean
- comments: Inline comments on specific files and lines
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 71 lines · 62 tokens per session scan A 3efc5a92ad43
gerrit-review is a skill published in the GitHub repository ambient-code/platform (131 stars, last pushed today), licensed MIT. It adds 62 tokens to every session and 797 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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